Through the use of engaging and detailed examples, the authors guide the reader through the use of the computer program LISREL to show how it can be applied to the analysis of interactions in regression framework. The authors consider a wide range of applications, including qualitative moderator variables, longitudinal designs, and product term analysis. They describe different types of measurement error, and follow this discussion with latent variable representations of measurement error that serve as the foundation for the analyses described in later chapters. They then offer a brief introduction to LISREL and show how it can be used to execute the analyses. Readers can use this book without any prior training in LISREL, and will find it an excellent introduction to analytic methods that deal with the problem of measurement error in the analyses of interactions.
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Dr. James Jaccard is Professor of Social Work at New York University Silver School of Social Work. He received his doctoral degree from the University of Illinois, Urbana, in 1976. Dr. Jaccard’s research focuses on adolescent and young adult problem behaviors, particularly those related to unintended pregnancy and substance use, broadly defined. He has developed parent-based interventions to teach parents how to more effectively communicate and parent their adolescent children so as to reduce the risk of unintended pregnancies and problems due to substance use. Dr. Jaccard has written numerous books and articles on the analysis of interaction effects in a wide range of statistical models and teaches advanced graduate courses on structural equation modeling. He has written influential articles on the issue of arbitrary metrics in social science research. Dr. Jaccard also has written about theory construction and how to build conceptual models in a book published by Guilford Press.
Through the use of engaging and detailed examples, the authors guide the reader through the use of the computer program LISREL to show how it can be applied to the analysis of interactions in regression framework. The authors consider a wide range of applications, including qualitative moderator variables, longitudinal designs, and product term analysis. They describe different types of measurement error, and follow this discussion with latent variable representations of measurement error that serve as the foundation for the analyses described in later chapters. They then offer a brief introduction to LISREL and show how it can be used to execute the analyses. Readers can use this book without any prior training in LISREL, and will find it an excellent introduction to analytic methods that deal with the problem of measurement error in the analyses of interactions.
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